Week 1 - Sept. 14

Module 1 Capturing & Creating Data

Location: Campus

Theme: How does the human past become data? What the hang is Digital Archaeology? Which flavour(s) of digital archaeology will we explore in this class?

Before you come to class: Colleen Morgan. 2022. Current Digital Archaeology. Annual Review Anthropology. 51:213-231. https://doi.org/10.1146/annurev-anthro-041320-114101 Read like a predator! Read the Introduction, then read the Conclusion. Then dive into anything else of interest: what captures your interest? What do you want to know more about?

The Plan:

• data vs data story activity, or, how I propose to learn something of who you are (and vice versa)
• Discussion
• Digital archaeology and the flavours of it that I practice - networks, simulations, computer vision, antiquities trade, space archaeology, archaeology impossible, practical necromancy
• Syllabus review, and the Billings Estate Project
  • mortuary archaeology, buildings archaeology
• nuts and bolts: getting your computer set up. Github, Google Collab, and possibly a variety of apps on your phone.

Skill Building:

First, let’s get set up with github.

Now, let’s build a dataset.

This activity owes much to the pedagogical practice of Brandon Walsh, Director of Student Programs at the Scholarslab, a leading research institute in the digital humanities at the University of Virginia. He uses it at the start of one of his own classes (see also his post on ‘personal data stories’).

You can pair up, you can divvy up, use whatever’s handy and you feel comfortable with sharing, I like a noisy classroom. What I like about this exercise, in the context of digital archaeology, is that it really gets you thinking about the connection between the subject - you - and the traces you leave behind.

• Identify your data
  • Who are you?
• Describe your data
  • What are you interested in describing as a part of your dataset? What are you not?
• Collect
  • Gather your data in one place.
• Clean
  • Edit the dataset so that it’s in a presentable, consistent format.
• Analyze
  • What stories are in your dataset?
• Distribute
  • How will you share it back to me?

(Brandon Waslh, Data for the Rest of Us).

Homework:

• by Friday noon, send your dataset to me (ie, upload it into your github repository, and use the form link on the assessment page to signal it is ready). For Monday, be prepared to talk about what challenged you, and if you can, why it challenged you. What kind of meaningful differences would exist in your dataset if you were documenting physical objects?

One last thought

There is a lot of emphasis in this course on keeping track of your thinking, your process, and the ephemera of your digital process. This is deliberate! Future You depends on Past You to have kept good records, because it is extremely easy to get sidetracked, explore dead ends, or forget why/what decisions you made along the way.